FAQPage vs QAPage: Which Schema for Your Review Questions?

What is the actual difference between FAQPage and QAPage?

The split is about who wrote the answers. FAQPage is for your own question-and-answer content, where you control both sides: you pose the question and you give the single authoritative answer. QAPage is for user-generated pages built around one question with a set of community answers, the way a product Q&A thread or a forum post works.

The quick test is to count the voices. One author answering many questions is FAQPage. Many people answering one question is QAPage. If you cannot say which it is, you are usually looking at FAQPage content dressed up as a discussion, and you should mark it as FAQPage.

When should I use FAQPage?

Use FAQPage when the answers are yours and final. A support page, a shipping-and-returns block, a sizing explainer, a feature page that addresses common objections: these are all one author speaking with authority, so they are FAQPage.

The rule that trips people up is the single-answer requirement. FAQPage expects exactly one answer per question. If a question genuinely has competing community answers, FAQPage is the wrong shape and Google may treat the markup as invalid.

• Store support and policy pages (returns, shipping, warranty).
• Product objection handling, where you answer the doubt a buyer has.
• Pricing or plan questions you answer in your own voice.
• Onboarding or how-it-works content with one settled answer each.

When should I use QAPage?

Use QAPage when the page is built around a single user question and the answers come from other people. A product question like "does this run small?" with several customer replies is the textbook case. The schema is designed to carry one Question and many possible answers, including an accepted answer and upvote counts.

This matters for merchants because customer questions on a product page are some of the most decision-shaping text you have. Marking them as QAPage tells search and answer engines that this is genuine community input, which is weighted differently from a brand talking about itself.

Does FAQ markup still earn a rich result?

Rarely now. Google narrowed FAQ rich-result display, so the expandable question list that used to appear under a result is mostly gone for ordinary sites and survives mainly for a small set of authoritative health and government domains.

That is not a reason to strip the markup out. The structured data still describes your content cleanly, and the dated point worth holding onto is that the markup still aids AI extraction even when no visual rich result shows. The block below sets out what changed and what to do about it.

• The on-page FAQ dropdown is no longer the reason to add the markup.
• The markup remains a clean, machine-readable statement of your Q&A.
• Answer engines lift well-structured Q&A passages directly into answers.
• Keep questions a buyer would actually type, not keyword stuffing.

Why does picking the right type still matter for AI answers?

Because the type sets the model's expectation of trust. QAPage signals independent, user-generated input, which answer engines lean on because an outside voice is more credible than a brand describing itself. FAQPage signals an authoritative, first-party answer, which is exactly what a model wants when the question is factual and settled.

Mislabel them and you blur that signal. A community thread marked as FAQPage reads like the brand wrote the customer praise, which is the opposite of the credibility you were trying to capture.

What happens if I use the wrong one?

At best the markup is ignored; at worst it is flagged as invalid in Search Console and earns nothing. FAQPage with multiple conflicting answers per question breaks the one-answer rule. QAPage with no real user question, just your own marketing copy, fails the user-generated test.

There is also a quieter cost. Marking promotional content as a customer Q&A to borrow the trust signal is the kind of thing that erodes credibility when an engine works out that the answers are not independent. Honesty in the markup is the safer long-term position.

How does this fit a review programme?

Reviews, customer questions, and your own FAQ are three different objects, and each has a schema that fits it: Review and AggregateRating for the reviews, QAPage for the customer questions, FAQPage for your own answers. Used correctly they corroborate each other, which is what search and AI weigh.

Most review apps were built for the on-page shopper and stop at rendering stars, so the question text and review text often never reach the page HTML in a form a model can read. Getting your existing reviews and customer questions readable, corroborated, and cited in search and AI is the gap BetterReviews is built to close.